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Organizational Performance and Capabilities to Analyze Big Data: Do the Ambidexterity and Business Value of Big Data Analytics Matter?

Author

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  • Aljumah, Ahmad Ibrahim
  • Nuseir, Mohammed T.
  • Alam, Md. Mahmudul

    (Universiti Utara Malaysia)

Abstract

Objective/Purpose: The aim of the study is to examine the impact of the big data analytics capabilities (BDAC) on the organizational performance. The study also examines the mediating role of ambidexterity and the moderating role of business value of big data (BVBD) analytics in the relationship between the big data analytics capabilities and the organizational performance. Methodology/Design: This study collected primary data based on a questionnaire survey among the large manufacturing firms operating in UAE. A total of 650 questionnaires were distributed among the manufacturing firms and 295 samples were used for final data analysis. The survey was conducted from September to November in 2019 and partial least squares structural equation modeling (PLS-SEM). Findings: The BDA scalability is supported by the findings on the performance of firm and its determinants such as system, value of business, and quality of information. The role of business value as a moderator and ambidexterity as mediator are found significant. The results reveal that there is a need for managers to consider the business value and quality dynamics as crucial strategic objectives to achieve high performance of the firm. Implications: The study has significant policy implication for practitioners and researchers for understanding the issues related to big data analytics. Originality/Value: This is an original study based on primary data from UAE manufacturing firms.

Suggested Citation

  • Aljumah, Ahmad Ibrahim & Nuseir, Mohammed T. & Alam, Md. Mahmudul, 2021. "Organizational Performance and Capabilities to Analyze Big Data: Do the Ambidexterity and Business Value of Big Data Analytics Matter?," OSF Preprints an8er, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:an8er
    DOI: 10.31219/osf.io/an8er
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    References listed on IDEAS

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    Cited by:

    1. Huynh, Minh-Tay & Nippa, Michael & Aichner, Thomas, 2023. "Big data analytics capabilities: Patchwork or progress? A systematic review of the status quo and implications for future research," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    2. Dignity Paradza & Olawande Daramola, 2021. "Business Intelligence and Business Value in Organisations: A Systematic Literature Review," Sustainability, MDPI, vol. 13(20), pages 1-27, October.
    3. Md Ahsan Uddin Murad & Dilek Cetindamar & Subrata Chakraborty, 2022. "Identifying the Key Big Data Analytics Capabilities in Bangladesh’s Healthcare Sector," Sustainability, MDPI, vol. 14(12), pages 1-21, June.
    4. Guixiang Cao & Xintong Fang & Ying Chen & Jinghuai She, 2023. "Regional Big Data Application Capability and Firm Green Technology Innovation," Sustainability, MDPI, vol. 15(17), pages 1-29, August.
    5. Corallo, Angelo & Crespino, Anna Maria & Del Vecchio, Vito & Gervasi, Massimiliano & Lazoi, Mariangela & Marra, Manuela, 2023. "Evaluating maturity level of big data management and analytics in industrial companies," Technological Forecasting and Social Change, Elsevier, vol. 196(C).

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